Combining fuzzy clustering and fuzzy inferencing in information retrieval

Abstract

We present an integrated approach to information retrieval which combines fuzzy clustering and fuzzy inference techniques in order to achieve optimal retrieval performance. To capture the relationships among index terms, fuzzy logic rules are used. We adapt several fuzzy clustering methods to the task of clustering documents with respect to the index terms. The clusters generated provide a basis for building the fuzzy logic rules. The clusters can also be used to form hyperlinks between documents. The fuzzy logic rules are applied with fuzzy inference to derive useful modifications of the initial query, which will guide the search for relevant documents. Alternative ways to use the fuzzy clusters are explored in this work as well. Our method combines fuzzy clustering and fuzzy inference with traditional relevance feedback approach for retrieval. The advantage of this approach is the emphasis on semantic information which relates the terms through the fuzzy clusters and fuzzy rules. A series of experiments have been conducted in order to validate this approach; a description of those experiments along with the results are presented.